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stat.ML2025
Compactly-supported nonstationary kernels for computing exact Gaussian processes on big data
Mark D. Risser, Marcus M. Noack, Hengrui Luo +1
The Gaussian process (GP) is a widely used probabilistic machine learning method with implicit uncertainty characterization for stochastic function approximation, stochastic modeli…
stat.ML2024
A Unifying Perspective on Non-Stationary Kernels for Deeper Gaussian Processes
Marcus M. Noack, Hengrui Luo, Mark D. Risser
The Gaussian process (GP) is a popular statistical technique for stochastic function approximation and uncertainty quantification from data. GPs have been adopted into the realm of…